Professor Charles Norman MacLeod

Electronic and Electrical Engineering


Personal statement

Charles MacLeod is a Professor in the Centre for Ultrasonic Engineering. 

He is the Babcock International Group / Royal Academy of Engineering Chair in Sensor-Driven Automated Welding.

He is director of the Sensor Enabled Automation & Robotics Control Hub (SEARCH), a £24M research innovation and technology transfer laboratory. Aligned to this, he is Course Director of the Autonomous Robotic Intelligent Systems (ARIS) MSc.

His research is primarily associated with the inspection and manufacturing enhancement of high-value assets and components, where he leads a number of high-profile inter-disciplinary in-process welding and metal additive research projects.

He has driven and co-developed core robotic and ultrasonic technology from fundamental EPSRC research, which is now being licensed by a leading industrial organisation and co-developed an innovative inspection robot for a critical life-extension inspection at Sellafield Reprocessing Facility.

He is the PI and designer of the Engaging Robotic Interactive Cell (ERIC) STEM Outreach cell. 

His research interests include:

Non-Destructive Evaluation

In-Process Inspection of Fusion Welding & Metal Additive Components

Sensors including Ultrasonic, Electromagnetic, Tactile and Visual

Automation & Robotics 

Automated Manufacturing & Welding

Teaching Activities.

Course Director: Autonomous Robotic Intelligent Systems (ARIS) MSc.

Module Registrar: EE987 Sensors & Instrumentation

Lecturer: EE312 Instrumentation and Microcontrollers 

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Single-bit reception with coded excitation for lightweight advanced ultrasonic imaging systems
Nicolson Ewan, Lines David, Mohseni Ehsan, MacLeod Charles Norman
IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control (2024)
A technique for medium-range through-thickness focusing using Lamb waves
Tzaferis Konstantinos, Dobie Gordon, Lines Dave, MacLeod Charles
NDT and E International Vol 145 (2024)
Unsupervised machine learning for flaw detection in automated ultrasonic testing of carbon fibre reinforced plastic composites
Tunukovic Vedran, McKnight Shaun, Pyle Richard, Wang Zhiming, Mohseni Ehsan, Pierce S Gareth, Vithanage Randika K W, Dobie Gordon, MacLeod Charles N, Cochran Sandy, O'Hare Tom
Ultrasonics Vol 140 (2024)
Innovative non-invasive ultrasound method for whisky cask liquid level measurement
Zhang Dayi, Jackson William, Dobie Gordon, MacLeod Charles, Gachagan Anthony
Measurement Vol 228 (2024)
A study of machine learning object detection performance for phased array ultrasonic testing of carbon fibre reinforced plastics
Tunukovic Vedran, McKnight Shaun, Mohseni Ehsan, Pierce S Gareth, Pyle Richard, Duernberger Euan, Loukas Charalampos, Vithanage Randika KW, Lines David, Dobie Gordon, MacLeod Charles N, Cochran Sandy, O'Hare Tom
NDT and E International Vol 144 (2024)
Three-dimensional residual neural architecture search for ultrasonic defect detection
McKnight Shaun, MacKinnon Christopher, Pierce S Gareth, Mohseni Ehsan, Tunukovic Vedran, MacLeod Charles N, Vithanage Randika K W, O'Hare Tom
IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control Vol 71, pp. 423-436 (2024)

More publications

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Professional Activities

Using In-Process NDE Inspection to Qualify WAAM Builds: Working towards Qualification for Different NDE Modalities
Flexible Robotics for Automated Non-Destructive Testing
Towards Flexible and Automated Robotic Multi-Pass Arc Welding
Royal Institute of Naval Architects Warship Conference - Invited Talk
Flexible Robotics to Inspect Aerospace Components​
A study of the accuracy and repeatability of mobile collaborative robots for non-destructive evaluations

More professional activities


Robotic laser ultrasonic inspection system for integration with a WAAM cell (Royce Industrial Collaboration Programme)
Stratoudaki, Theodosia (Principal Investigator) MacLeod, Charles Norman (Co-investigator) Pierce, Gareth (Co-investigator)
01-Jan-2023 - 31-Jan-2024
DTP 2224 University of Strathclyde | Macleod, James
MacLeod, Charles Norman (Principal Investigator) Dobie, Gordon (Co-investigator) Macleod, James (Research Co-investigator)
01-Jan-2023 - 01-Jan-2027
Improving Ultrasonic Imaging using Machine Learning - FIND CDT EngD with Rolls Royce
Tant, Katherine Margaret Mary (Principal Investigator) MacLeod, Charles Norman (Co-investigator)
01-Jan-2023 - 30-Jan-2027
Digital Twin for Manufacturing and Image Processing
Loukas, Charalampos (Principal Investigator) MacLeod, Charles Norman (Principal Investigator)
Summer internship project for the student Eleanor Smith (4rth year). I am supervising the student who works on the area of digital twin for manufacturing and real-time image processing for robotic welding.
26-Jan-2023 - 30-Jan-2023
Multi-Modal Sensing for Heavy-Manufacturing Robotic Welding
Loukas, Charalampos (Principal Investigator) MacLeod, Charles Norman (Principal Investigator)
Fusion welding of metals is a joining method fundamental to High-Value Manufacturing (HVM). Distinctive challenges such as the global shortage of welders and the increasing requirement for high-integrity components in the energy and defence sectors fuel the need to research and adopt digital welding
technologies such as sensor-enabled robotic welding. Surface and volumetric sensing approaches at the point of manufacture coupled with real-time robotic motion offer the possibility to control, adapt and consistently ensure defect-free fusion. This project seeks to investigate novel event-based neuromorphic vision sensing coupled to high-temperature in-process ultrasonic imaging to deliver high-integrity welds right the first time.

26-Jan-2023 - 30-Jan-2023
Residual stress measurement round robin on a wire arc additively manufactured titanium alloy
Javadi, Yashar (Principal Investigator) Sun, Yongle (Co-investigator) Alipooramirabad, Houman (Co-investigator) MacLeod, Charles Norman (Co-investigator) Reid, Mark (Co-investigator)
The aim of this project is the development of a round-robin residual stress measurement to investigate the residual stress in ‎titanium (Ti–6Al–4V) Wire + Arc Additive Manufacture (WAAM) ‎components. Cranfield will contribute with the manufacturing and finite element modelling of the WAAM samples. ‎ANSTO is supporting the project with residual stress measurement using Neutron Diffraction (ND) method‎.
21-Jan-2023 - 21-Jan-2023

More projects

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Professor Charles Norman MacLeod
Electronic and Electrical Engineering

Tel: Unlisted